Using Geospatial Data in R {https://t.co/KWcGGuga86} #rstats #DataScience
— R-bloggers (@Rbloggers) June 11, 2021
How to structure your data workflow efficiently using R {https://t.co/1uYfk6oxXJ} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
Bayesian Linear Regression with Gibbs Sampling using R code {https://t.co/DBkKEAExyt} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
Understanding Logistic Regression {https://t.co/GhfsV0DGF3} #rstats #DataScience
— R-bloggers (@Rbloggers) June 11, 2021
Functional PCA with R {https://t.co/plIRTBZ0zq} #rstats #DataScience
— R-bloggers (@Rbloggers) June 11, 2021
Retrieving Stock Price using R {https://t.co/0NIUaNMUaP} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
Lasso Regression Model with R code {https://t.co/7gylAZ2WQ0} #rstats #DataScience
— R-bloggers (@Rbloggers) June 12, 2021
DTPlyr – easier data.table for DPLYR users {https://t.co/GaoJf1V6iE} #rstats #DataScience
— R-bloggers (@Rbloggers) June 8, 2021
Hierarchical forecasting of hospital admissions- ML approach (screen variables) {https://t.co/jfO8k91tqu} #rstats #DataScience
— R-bloggers (@Rbloggers) June 12, 2021
Spatiotemporal modeling and real-time prediction of origin-destination traffic demand {https://t.co/l1aosNJ5QL} #rstats #DataScience
— R-bloggers (@Rbloggers) June 10, 2021
Taking text data to the next level – Unsupervised and supervised approaches in NLP @ {https://t.co/R5dMo1tMxm} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
Kurtosis in R-What do you understand by Kurtosis? {https://t.co/O4jkM1YJ7X} #rstats #DataScience
— R-bloggers (@Rbloggers) June 8, 2021
Big Book of R has over 200 books! {https://t.co/uIeAiWl5Gr} #rstats #DataScience
— R-bloggers (@Rbloggers) June 5, 2021
Sentiment analysis in R {https://t.co/HoyxGDHj7J} #rstats #DataScience
— R-bloggers (@Rbloggers) May 16, 2021
Using Geospatial Data in R {https://t.co/KWcGGuga86} #rstats #DataScience
— R-bloggers (@Rbloggers) June 11, 2021
How to structure your data workflow efficiently using R {https://t.co/1uYfk6oxXJ} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
How to find dataset differences in R Quickly Compare Datasets {https://t.co/tU2Bjh416q} #rstats #DataScience
— R-bloggers (@Rbloggers) May 25, 2021
GitHub With R {https://t.co/ZC5n2jnMAO} #rstats #DataScience
— R-bloggers (@Rbloggers) May 16, 2021
Build and improve a Machine Learning Classification model with TidyModels and R {https://t.co/lNBLmSpyHm} #rstats #DataScience
— R-bloggers (@Rbloggers) May 25, 2021
New features in R 4.1.0 {https://t.co/wmYN0OHixh} #rstats #DataScience
— R-bloggers (@Rbloggers) May 18, 2021
Bayesian Linear Regression with Gibbs Sampling using R code {https://t.co/DBkKEAExyt} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
Understanding Logistic Regression {https://t.co/GhfsV0DGF3} #rstats #DataScience
— R-bloggers (@Rbloggers) June 11, 2021
Functional PCA with R {https://t.co/plIRTBZ0zq} #rstats #DataScience
— R-bloggers (@Rbloggers) June 11, 2021
Retrieving Stock Price using R {https://t.co/0NIUaNMUaP} #rstats #DataScience
— R-bloggers (@Rbloggers) June 13, 2021
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```